AI ML Engineer
Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Aug 4, 2026.
Onsitefull time·Req 26-02568·Posted 1 month ago
AI ML Engineer
Direct Placement role in Columbus, GA. Onsite engagement, matched and submitted by an ApTask vertical recruiter.
LocationColumbus, GA · Onsite
Compensation$85k-$90k/yr
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Your résumé routes to the vertical recruiter who owns this requisition. Identity-verified profile, never resold or syndicated.
Stack
- ML
- AI
About the role
Direct Placement role in Columbus, GA. Onsite engagement, matched and submitted by an ApTask vertical recruiter.
About technology at ApTask
What this vertical looks like inside ApTask.
Technology roles at ApTask cover the software, cloud, data, security, and platform-engineering functions that power Fortune 500 digital operations. Our recruiters specialise in high-signal technical calibration - every candidate is validated against the specific stack, framework versions, and deployment context the client runs, not a keyword match. Our largest engagements sit inside AWS, Azure, GCP, Snowflake, Databricks, and modern data-mesh estates. Because we route through Fieldglass, Beeline, Workday VNDLY, and Coupa VMS, technology contractors placed through ApTask carry MBE diversity spend against the client's supplier program while remaining W-2 with full benefits under our payroll.
How it works
What happens after you apply.
1. Verified profile
Submit your résumé and complete the ApTask identity + skills verification. We check right-to-work, background, and technical calibration once - never resell or re-verify - so future roles surface faster.
2. Recruiter calibration call
Within one business day, the recruiter who owns this requisition reviews your profile against the client's specific stack, arrangement, and start-date requirements. You'll hear back either way - no ghosting.
3. Client interview
If your profile is a fit, we present you to the hiring team. Most clients run 2-3 interview stages: hiring-manager screen, technical panel, and final. We prep you with the exact scorecard criteria before each round.
4. Offer + onboarding
On acceptance, you onboard W-2 with ApTask (contract) or direct-hire with the client (per role type). Benefits, payroll, and timesheets run through us. Your recruiter stays your point of contact for the length of the engagement.
Frequently asked
Questions candidates ask about this role.
Is the AI ML Engineer role on-site?Yes - this role is on-site at the client's Columbus, GA location, five days per week. The client's culture and delivery cadence are calibrated around in-person collaboration for this position. Relocation support may be available for the right candidate; the recruiter will confirm during your calibration call.
Is this a permanent role?Yes - this is a full time direct-hire position with the client. On offer acceptance, you onboard directly onto the client's payroll and benefits. ApTask's role is placement only; the recruiter stays in touch for the first 90 days as a check-in, but your day-to-day relationship is with the client's hiring manager.
What is the compensation range for this role?The advertised range for this AI ML Engineer role is $85,000-$90,000 per year. Where you land within the band depends on validated experience, the specific stack calibration match, and - for contract engagements - the bill-rate the client has locked in for this requisition. The recruiter will discuss the exact number during your calibration call.
How quickly does the interview process move?If your profile is a fit for this role, you can expect the recruiter's first call within one business day. From there, interview cadence depends on the client's hiring-manager and panel availability. Total time from submission to signed offer varies by client - pre-verified profiles and calibrated submissions cut the noise, but the pace of interviews is driven by the client, not us.
What technical skills does the AI ML Engineer role require?
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Your résumé routes to the recruiter who owns this requisition. Identity-verified once, matched against every future ApTask role that fits your stack.
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